• Imaging Science in Dentistry
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• v.49 no.2
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• pp.139-151
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• 2019

Purpose: This study was performed to investigate the effect of exposure parameters on image quality obtained using a cone-beam computed tomography (CBCT) scanner and the relationship between physical factors and clinical image quality depending on the diagnostic task. Materials and Methods: CBCT images of a SedentexCT IQ phantom and a real skull phantom were obtained under different combinations of tube voltage and tube current (Alphard 3030 CBCT scanner, 78-90 kVp and 2-8 mA). The images obtained using a SedentexCT IQ phantom were analyzed technically, and the physical factors of image noise, contrast resolution, spatial resolution, and metal artifacts were measured. The images obtained using a real skull phantom were evaluated for each diagnostic task by 6 oral and maxillofacial radiologists, and each setting was classified as acceptable or unacceptable based on those evaluations. A statistical analysis of the relationships of exposure parameters and physical factors with observer scores was conducted. Results: For periapical diagnosis and implant planning, the tube current of the acceptable images was significantly higher than that of the unacceptable images. Image noise, the contrast-to-noise ratio (CNR), the line pair chart on the Z axis, and modulation transfer function (MTF) values showed statistically significant differences between the acceptable and unacceptable image groups. The cut-off values obtained using receiver operating characteristic curves for CNR and MTF 10 were useful for determining acceptability. Conclusion: Tube current had a major influence on clinical image quality. CNR and MTF 10 were useful physical factors that showed significantly associations with clinical image quality.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.2
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• pp.35-52
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• 2024

This study conducted an assessment of potential impacts on the drought in agricultural reservoirs using the recently proposed SSP (Shared Socioeconomic Pathways) scenarios by IPCC (Intergovernmental Panel on Climate Change). This study assesses the potential impact of climate change on agricultural water resources and infrastructure vulnerability within Gyeongsangnam-do, focusing on 15 agricultural reservoirs. The assessment was based on the KRC (Korea Rural Community Corporation) 1^st vulnerability assessment methodology using RCP scenarios for 2021. However, there are limitations due to the necessity for climate impact assessments based on the latest climate information and the uncertainties associated with using a single scenario from national standard scenarios. Therefore, we applied the 13 GCM (General Circulation Model) outputs based on the newly introduced SSP scenarios. Furthermore, due to difficulties in data acquisiton, we reassessed potential impacts by redistributing weights for proxy variables. As a main result, with lower future potential impacts observed in areas with higher precipitation along the southern coast. Overall, the potential impacts increased for all reservoirs as we moved into the future, maintaining their relative rankings, yet showing no significant variability in the far future. Although the overall pattern of potential impacts aligns with previous evaluations, reevaluation under similar conditions with different spatial resolutions emphasizes the critical role of meteorological data spatial resolution in assessments. The results of this study are expected to improve the credibility and accuracy formulation of vulnerability employing more scientific predictions.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1615-1633
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• 2023

Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.

• Investigative Magnetic Resonance Imaging
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• v.10 no.2
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• pp.89-97
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• 2006

Purpose : To evaluate MR image qualities we developed a new MRI phantom with the fixation structures necessary to position it into coil firmly. Materials and methods : We designed MRI phantom for eight evaluation items such as slice thickness accuracy, high contrast spatial resolution, low contrast object detectability, geometry accuracy, slice position accuracy, image intensity uniformity, percent signal ghosting and signal to noise ratio. For the positioning of phantom at coils, the fixation structures were set up on the surface of phantom. Six different MRI units were used for test the possibility for the clinical application and their image qualities were evaluated. Results : We acquired appropriate MR image qualities enough for the evaluation on all used MR units and confirmed that their evaluations were within reliable values compared to real ones for some items. The positioning of our phantom into head coils with fixation structures worked well for proper imaging. Conclusion : We found that our prototype of MRI phantom had the possibility of clinical application for MR image quality assessment.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.204-210
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• 2013

The patients who had been operated total mastectomy are different from general women in their breasts thickness due to breast surgery. As a result, digital chest image from total mastectomy patients will be different attenuation. The main objective for this study is to show that a proper Ion chamber standard combination measuring MTF which is objective basis for Digital image, when be x-ray for total mastectomy patient. We have designed the unique number that shown Left is 1, Right is 2, Center is 3 and have put the edge phantom on detector ion chamber. Lastly, we have obtained experiment images. The evaluations of all image quality have measured by 50% MTF of spatial resolution and absorption dose using Matlab(R2007a). The result showed that average exposure condition, MTF value, absorption dose for 1+3 and 2+3 combinations were 2.745 mAs, 1.925 lp/mm, 0.688 mGy. Consequently, that showed high MTF, DQE and low dose than other combinations. Therefore, a proper changes of ion chambers are able to improve image quality and to reduce radiation exposure when be X-ray for total mastectomy patients. Also, it will be possible to standard for application chamber combination and utilization on clinical detection.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.49-58
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• 2015

Up to the present point in time, the level diagnosis system for urban reactivation have utilized various methods for establishment and management in Korea and overseas, such as city competitiveness evaluation, urban decay diagnosis, etc. However, contrary to performing diagnosis and evaluations on general cities in existing studies, it is found to be a very complex and difficult task to perform a diagnosis on the level of U-City due to its unique characteristics. It is difficult to determine the level of a U-City using a level diagnosis system used for general cities because a U-City is comprised of a connection/fusion of various structural elements. Therefore, in order to perform a systematic diagnosis of a U-City, it is necessary to primarily observe the structural characteristics of a U-city to derive a diagnosis system based on the relativity between each structural element. This study aims to propose a directivity of a U-City level diagnosis system in comprehensive consideration of various elements, such as the objective of a U-City, as well as the structural elements that compose a U-City based on the definitions prescribed in U-City legislations, including ubiquitous city planning, ubiquitous city infrastructure, ubiquitous city technology, services, etc. The results of this study are expected to provide a resolution for the regional quality differences of U-Cities, and also establish a stepping-stone for the realization of U-Cities with high degree of completion.